Total 50,888 skills, AI & Machine Learning has 8520 skills
Showing 12 of 8520 skills
Guide for creating, refactoring, and optimizing AGENTS.md files (and CLAUDE.md files) for AI coding agent repositories. Use when the user wants to create a new AGENTS.md, refactor an existing one, audit their AGENTS.md for bloat or staleness, apply progressive disclosure principles, set up AGENTS.md in a monorepo, or improve how their AI coding agents behave via repository configuration files. Also applies to CLAUDE.md files (Claude Code's equivalent).
Query decomposition for multi-concept retrieval. Use when handling complex queries spanning multiple topics, implementing multi-hop retrieval, or improving coverage for compound questions.
Agentic workflow patterns for autonomous LLM reasoning. Use when building ReAct agents, implementing reasoning loops, or creating LLMs that plan and execute multi-step tasks.
Create Manim animations for demo videos. Use when visualizing agent workflows, skill pipelines, or architecture diagrams as animated MP4 overlays
Translate text between English and Indian languages using Sarvam AI's Mayura model. Use when the user needs to translate content, localize applications, or convert text between Hindi, Tamil, Bengali, Telugu, and 7 other Indian languages. Supports bidirectional translation, script control, and code-mixed text.
xAI Grok API authentication and setup. Use when configuring xAI API access, setting up API keys, or troubleshooting authentication issues.
Execute real actions across 1000+ applications (Gmail, Slack, GitHub, Notion, etc.) using Composio's tool routing. Stop suggesting—start doing.
Fine-tune models on your data to maximize quality and cut costs. Use when prompt optimization hit a ceiling, you need domain specialization, you want cheaper models to match expensive ones, you heard "fine-tuning will make us AI-native", you have 500+ training examples, or you need to train on proprietary data. Covers DSPy BootstrapFinetune, BetterTogether, model distillation, and when to fine-tune vs optimize prompts.
Amazon Bedrock Model Customization with fine-tuning, continued pre-training, reinforcement fine-tuning (NEW 2025 - 66% accuracy gains), and distillation. Create customization jobs, monitor training, deploy custom models, and evaluate performance. Use when customizing Claude, Titan, or other Bedrock models for domain-specific tasks, adapting to proprietary data, improving accuracy on specialized workflows, or distilling large models to smaller ones.
Create agent skills for Microsoft technologies using Learn MCP tools. Use when users want to create a skill that teaches agents about any Microsoft technology, library, framework, or service (Azure, .NET, M365, VS Code, Bicep, etc.). Investigates topics deeply, then generates a hybrid skill storing essential knowledge locally while enabling dynamic deeper investigation.
Design short-term, long-term, and graph-based memory architectures
Integrate with Affinda's document AI API to extract structured data from documents (invoices, resumes, receipts, contracts, and custom types). Covers authentication, client libraries (Python, TypeScript), structured outputs with Pydantic models and TypeScript interfaces, webhooks, upload patterns, and the full documentation map. Use when building integrations that parse, classify, or extract data from documents using Affinda.